Immune intrinsic escape signature stratifies prognosis, characterizes the tumor immune microenvironment, and identifies tumorigenic PPP1R8 in glioblastoma multiforme patients.

BACKGROUND

Glioblastoma (GBM) is a highly aggressive brain tumor with poor prognosis and limited response to immunotherapy. Immune escape-related genes (IERGs) are increasingly recognized as critical regulators of tumor progression and immune evasion. However, their prognostic value in GBM remains unclear. This study aims to evaluate the clinical relevance of IERGs and develop a predictive gene signature to guide prognosis and characterize the tumor immune microenvironment (TIME).

METHODS

We performed a comprehensive analysis of IERGs using the TCGA GBM dataset. Prognostic IERGs were identified through univariate Cox regression, and a multivariate Cox model was used to develop a prognostic signature. Risk scores (IEScore) were calculated to classify patients into high- and low-risk groups. The signature was validated in two independent GBM cohorts. Its prognostic independence was assessed after adjusting for clinicopathological features. Receiver operating characteristic (ROC) analysis confirmed the signature's reliability. TIME analysis was carried out using multiple deconvolution algorithms. Additionally, functional assays including CCK8, cell cycle, and apoptosis assays were conducted on PPP1R8-silenced U251 cells using CRISPR/Cas9 technology.

RESULTS

Thirty-six IERGs were associated with GBM outcomes, with 20 linked to poor survival and 16 to better outcomes. Key genes, including STAT2, IFNGR2, and PPP1R8, formed a robust prognostic signature. High-risk patients had significantly poorer overall survival (OS) compared to low-risk patients. The signature showed strong predictive power with AUC values of 0.68, 0.73, and 0.76 for 2-, 3-, and 5-year survival, respectively. Validation in two independent cohorts confirmed its robustness. Immune cell infiltration analysis revealed distinct patterns in high- and low-risk groups, with the high-risk group showing a more aggressive and immunosuppressive tumor microenvironment. The signature also effectively stratified low-grade glioma patients across four independent datasets. Knockout of PPP1R8 in GBM cells using CRISPR/Cas9 inhibited cell proliferation and increased apoptosis.

CONCLUSION

The IERGs-based signature offers reliable prognostication for GBM, validated across multiple datasets. It can guide patient stratification and inform therapeutic decisions for GBM and potentially low-grade gliomas (LGG). Furthermore, we identify PPP1R8 as a key regulator of GBM cell proliferation and growth, providing insights into the immune microenvironment's role in GBM progression.